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Two estimators of the mean of a counting process with panel count data

面板计数数据下计数过程均值的两种估计量

We study two estimators of the mean function of a countingprocess based on “panel count data.” The setting for “panel count data” is one in which $n$ independent subjects, each with a counting process with common mean function, are observed at several possibly different times duringa study. Following a model proposed by Schick and Yu, we allow the number of observation times, and the observation times themselves, to be random variables. Our goal is to estimate the mean…

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Optimal Nonparametric Estimation of First-price Auctions

第一价格拍卖中的最优非参数估计

This paper proposes a general approach and a computationally convenient estimation procedure for the structural analysis of auction data. Considering first-price sealed-bid auction models within the independent private value paradigm, we show that the underlying distribution of bidders' private values is identified from observed bids and the number of actual bidders without any parametric assumptions. Using the theory of minimax, we establish the best rate of uniform…

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Box-Cox quantile regression and the distribution of firm sizes

Box–Cox 分位数回归与企业规模分布

Using the Box–Cox quantile regression model, we analyse the size distribution of firms in Portuguese manufacturing during the 1980s. Specifically, we estimate the effect of selected industry attributes on the location, scale, skewness and kurtosis of the conditional size distributions of firms. We find that industry attributes affect the size of firms in the same direction across the distribution, but the effects of these variables are typically much greater at the largest…

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Linear household technologies

线性家庭技术

This paper discusses, estimates and formally compares the best known procedures for incorporating demographic variables into complete demand systems. In particular, a class of general procedures belonging to Gorman's family of 'general linear household technologies' is introduced. Estimation and comparison of different procedures make use of Italian household budget data for the years 1973-1992, incorporating a single demographic variable (family size) into a Generalized…

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Inference for Generalized Gini Indices Using the Iterated-Bootstrap Method

使用迭代自助法对广义基尼指数进行推断

Inference using the iterated-bootstrap method proposed by Hall is appealing for cases in which the percentile method needs to be used but the nominal level of a confidence interval has to be adjusted. One natural application is for generalized Gini indices of income inequality. When applying these theoretical inequality measures directly to sample data for the purpose of statistical inference, economists must come up with some measure of sampling variation. This is…

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The Demand for Lotto: The Role of Conscious Selection

乐透彩票需求:主动选号的作用

This article presents estimates of the elasticity of demand for lottery tickets using time series data in which there is variation in the expected value of a lottery ticket induced by rollovers. An important feature of our data is that there are far more rollovers than expected given the lottery design. We find strong evidence that individuals do not choose their lottery numbers uniformly from a uniform distribution—that is, conscious selection. We use our estimates to…

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SIMULTANEOUS EQUATIONS WITH INCOMPLETE PANELS

不完整面板下的联立方程估计

This paper compares the performance of several single and system estimators of a two equation simultaneous model with unbalanced panel data. The Monte Carlo design varies the degree of unbalancedness in the data and the variance components ratio due to the individual effects. One useful result for applied researchers is that the feasible error components 2SLS and 3SLS procedures based on simple ANOVA type estimators of the variance components perform well with incomplete…

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Inferences for a semiparametric model with panel data

面板数据半参数模型的统计推断

In a longitudinal study, suppose that, for each subject, repeated measurements of the response variable and covariates are collected at a set of distinct, irregularly spaced time points. We consider a semiparametric model which relates the mean of the response variable at each time point proportionally to a function of a time-dependent covariate vector to analyse such panel data. Inference procedures for regression parameters are proposed without involving any nonparametric…

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Nonparametric Analysis of Randomized Experiments with Missing Covariate and Outcome Data

协变量和结局缺失的随机实验非参数分析

Analysis of randomized experiments with missing covariate and outcome data is problematic, because the population parameters of interest are not identified unless one makes untestable assumptions about the distribution of the missing data. This article shows how population parameters can be bounded without making untestable distributional assumptions. Bounds are also derived under the assumption that covariate data are missing completely at random. In each case the bounds…

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Analyzing a Randomized Cancer Prevention Trial with a Missing Binary Outcome, an Auxiliary Variable, and All-or-None Compliance

含缺失二元结局、辅助变量与全有或全无依从性的随机癌症预防试验分析

The Prostate Cancer Prevention Trial is a randomized chemoprevention trial designed to compare the effect of daily finasteride versus placebo on prostate cancer determined by biopsy. Investigators have scheduled a biopsy at the end of the trial in 7 years or following a positive prostate-specific antigen (PSA) on annual screening. The analysis will need to adjust for two likely complications. First, some subjects will not receive a biopsy, depending in part on whether or not…

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Analyzing a Randomized Cancer Prevention Trial with a Missing Binary Outcome, an Auxiliary Variable, and All-or-None Compliance

结局缺失、辅助变量及全有或全无依从下的随机癌症预防试验分析

The Prostate Cancer Prevention Trial is a randomized chemoprevention trial designed to compare the effect of daily finasteride versus placebo on prostate cancer determined by biopsy. Investigators have scheduled a biopsy at the end of the trial in 7 years or following a positive prostate-specific antigen (PSA) on annual screening. The analysis will need to adjust for two likely complications. First, some subjects will not receive a biopsy, depending in part on whether or not…

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Scale economies in electricity distribution: a semiparametric analysis

配电规模经济的半参数分析

We estimate the costs of distributing electricity using data on municipal electric utilities in Ontario, Canada for the period 1993-5. The data reveal substantial evidence of increasing returns to scale with minimum efficient scale being achieved by firms with about 20,000 customers. Larger firms exhibit constant or decreasing returns. Utilities which deliver additional services (such as water|sewage), have significantly lower costs, indicating the presence of economies of…

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Large sample theory of maximum likelihood estimates in semiparametric biased sampling models

半参数偏倚抽样模型中最大似然估计的大样本理论

Vardi [Ann.Statist.13 178-203 (1985)] introduced an $s$-sample biased sampling model with known selection weight functions, gave a condition under which the common underlying probability distribution $G$ is uniquely estimable and developed simple procedure for computing the nonparametric maximum likelihood estimator (NPMLE) $\mathbb{G}_n$ of $G$. Gill, Vardi and Wellner thoroughly described the large sample properties of Vardi’s NPMLE, giving results on uniform consistency,…

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Latent Separability: Grouping Goods without Weak Separability

潜在可分性:不依赖弱可分性的商品分组

This paper develops a new concept of separability with overlapping groups. This is shown to provide a useful empirical and theoretical framework for investigating the grouping of goods and prices. It is a generalisation of weak separability in which goods are allowed to enter more than one group and where the composition of groups is identified by the choice of group specific exclusive goods. For the Almost Ideal and Translog demand models and their generalisations, we…

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Multiple comparisons with the best, with economic applications

与最优者的多重比较及其经济应用

In this paper we discuss a statistical method called multiple comparisons with the best, or MCB. This paper is meant to introduce MCB to economists. We discuss possible uses of MCB in economics. The application that we treat in most detail is the construction of confidence intervals for inefficiency measures from stochastic frontier models with panel data. We also consider an application to the analysis of labour market wage gaps. Copyright � 2000 John Wiley & Sons, Ltd.

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Two-sample quantile tests under general conditions

一般条件下的两样本分位数检验

A simple, nonparametric two-sample test for equality of a given collection of quantiles is developed which can be applied to a variety of empirical distribution functions, including the Kaplan-Meier estimator, a self-consistent estimator for doubly-censored data and an estimator for repeated measures data. The null hypothesis tested is that the quantiles are equal but other aspects of the distributions may differ between the two samples. This procedure can also be applied to…

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Bias and efficiency loss due to misclassified responses in binary regression

二元回归中响应误分类导致的偏差与效率损失

Methods that ignore errors in binary responses yield biased estimators of the associations of covariates with response. This paper derives general expressions for the magnitude of the bias due to errors in the response and shows that, unless both the sensitivity and specificity are very high, ignoring errors in the responses will yield highly biased covariate effect estimators. When the true, error-free response follows a generalised linear model and misclassification…

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Goodness of Fit and Related Inference Processes for Quantile Regression

分位数回归的拟合优度及相关推断过程

We introduce a goodness-of-fit process for quantile regression analogous to the conventional R2 statistic of least squares regression. Several related inference processes designed to test composite hypotheses about the combined effect of several covariates over an entire range of conditional quantile functions are also formulated. The asymptotic behavior of the inference processes is shown to be closely related to earlier p-sample goodness-of-fit theory involving Bessel…

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Dimension Reduction in Binary Response Regression

二元响应回归中的降维

The idea of dimension reduction without loss of information can be quite helpful for guiding the construction of summary plots in regression without requiring a prespecified model. Focusing on the central subspace, we investigate such “sufficient” dimension reduction in regressions with a binary response. Three existing methods—sliced inverse regression, principal Hessian direction, and sliced average variance estimation—and one new method—difference of covariances—are…

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A New Skewed Link Model for Dichotomous Quantal Response Data

二元响应数据的一类新偏斜链接模型

The logit, probit, and student t-links are widely used in modeling dichotomous quantal response data. Most of the commonly used link functions are symmetric, except the complementary log-log link. However, in some applications the overall fit can be significantly improved by the use of an asymmetric link. In this article we propose a new skewed link model for analyzing binary response data with covariates. Introducing a skewed distribution for the underlying latent variable,…

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Causal Effects in Nonexperimental Studies: Reevaluating the Evaluation of Training Programs

非实验研究中的因果效应:重新评估培训项目评价

This article uses propensity score methods to estimate the treatment impact of the National Supported Work (NSW) Demonstration, a labor training program, on postintervention earnings. We use data from Lalonde's evaluation of nonexperimental methods that combine the treated units from a randomized evaluation of the NSW with nonexperimental comparison units drawn from survey datasets. We apply propensity score methods to this composite dataset and demonstrate that, relative to…

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